Real-world analog signals such as temperature, pressure, sound, or light are routinely converted to a digital representation that can be easily processed in modern digital signal processing systems. The circuits that perform this conversion of an analog input signal to a digital output signal are analog-to-digital converters (ADCs). ADCs can translate analog electrical signals representing real-world phenomena such as temperature, pressure, sound, or light to digital signals for data processing purposes.
Designing an ADC is a non-trivial task because each application may have different needs in speed, performance, power, cost and size. As the applications needing ADCs grow, the need for fast, accurate, and reliable conversion performance also grows.
One application where ADCs are used are image sensors, or cameras, implementing phase-detection autofocus (PDAF). Such image sensors are also known as “dual pixel” image sensors.
When a PDAF camera acquires an image, light incident on the light sensors (e.g., photodetectors) of the camera is converted to charge, which charge is accumulated in the light sensors. Voltage representative of the charges accumulated on the light sensors may then be read out, possibly amplified using an amplifier, and analog values representing the voltages may be converted to digital values by an ADC. In some implementations, a technique known as “correlated multiple sampling” (CMS) may be implemented as the charges on photodiodes are converted to digital values, in order to minimize the noise contribution. In general, CMS is a sampling method used with complementary metal oxide semiconductor (CMOS) image sensors, based on repeatedly integrating and averaging the photodiode output in the analog domain.
Increasing the speed at which ADCs perform the necessary conversions in PDAF image sensors is always desirable.